WO2020049342A1

WO2020049342A1 - Wireless device indentification and tracking

Info

Publication number: WO2020049342A1
Application number: PCT/IB2018/056819
Authority: WO
Inventors: Reza FARRAHI MOGHADDAM; Fereydoun FARRAHI MOGHADDAM; Adriano MATOS PINHEIRO
Original assignee: Telefonaktiebolaget LM Ericsson AB
Current assignee: Telefonaktiebolaget LM Ericsson AB
Priority date: 2018-09-06
Filing date: 2018-09-06
Publication date: 2020-03-12
Anticipated expiration: 2021-03-06

Abstract

Apparatuses and methods for identifying and/or tracking red drones are provided. In one embodiment, a method in a management mode operating in a control plane of a wireless communication network includes, if registration of an unregistered wireless device fails, initiating collection of data associated with the unregistered wireless device. A virtual identifier is generated for the unregistered wireless device based on the collected data, and tracking of a spatial location of the unregistered wireless device is initiated using the virtual identifier.

Description

WIRELESS DEVICE IDENTIFICATION AND TRACKING

TECHNICAL FIELD

Methods and apparatuses for tracking and/or identifying wireless devices such as drones.

BACKGROUND

5^th Generation (5G) wireless communication standard (also referred to as new radio (NR)) is a convergence of many heterogeneous challenges of the future beyond the traditional telecom challenges. Low-latency, high-bandwidth, multiple-slice per wireless device, On-demand prioritization of resources (e.g., network, computing and/or storage resources, among others), and so on are features of some 5G solutions that may not co-exist all in the same use case or real life situation.

FIG. 1 is a diagram of example non-roaming Next Generation (NextGen or “NG”) reference architecture described in Third Generation Partnership Project (3 GPP) Technical Report (TR) 23.799 (3 GPP TR 23.799). The NG architecture includes several network functions and several reference points (NG1-NG15), which may indicate interfaces between the network functions. The NG architecture shown in FIG. 1 includes:

1. AMF: Core Access and Mobility Management Function: This function handles the mobility management.

2. SMF: Session Management Control Function: This function handles the session management. SMF interacts via NG4 with the User Plane Function (UPF).

3. AMF and SMF work under, via NG8, NG10, and NG12, the Authentication Server Function (AUSF) and the Unified Data Management (UDM). UDM supports the Authentication Credential Repository and Processing Function (ARPF), which stores the long-term security credentials.

4. PCF: Policy Control Function: This function is responsible for policy control in order to support Quality of Service (QoS).

5. AF: Application Function: This function provides information on packet flow to the PCF. 6. AUSF: Authentication Server Function: This function stores data for authentication of the wireless device (WD).

7. UPF: User Plane Function: This function supports user plane operations.

8. UDM: User Data Management; This function stores subscription data of the wireless device.

9. AF: Application Function: This function may provide session related information to the PCF.

10. DN: Data Network: may identify service provider services, Internet access or third-party services.

11. RAN: may be a network node using one or more radio access

technologies (RAT).

Historically, along the evolution path of mobile telephony from 2^nd generation (2G) toward 5G, telecom principles have governed the development of models and standards leading to 5G. This has resulted in standalone or non- standalone/roaming as described in 3GPP TR 23.799. Although this is an advantage point in terms of consistency, it also may be a hindrance in some use cases since it has been designed within the telecom principles.

There has also been development of Universal Traffic Management (UTM) for unmanned/manned vehicles. It is expected that UTM and 5G will converge at some point in the future, but existing systems still have not gotten this far. With the advancement of drone/unmanned aerial system (UAS) technology and their large physical impact (e.g., danger, liability, among others) compared to more physically- passive traditional wireless devices, it may be prudent to track and monitor wireless devices such as drones/UASs, and in general all wireless devices, both

authenticated/registered and unauthenticated/unregistered.

SUMMARY

Some embodiments advantageously provide methods and apparatuses for a wireless communication network to identify and/or track unregistered wireless devices, such as unregistered UASs. In some embodiments, the methods and apparatuses disclosed herein provide for a management node in the control plane of a wireless communication network that facilitates identifying and tracking unregistered wireless devices detected in the network coverage area based on, for example, analysis of spectral characteristics of signals received from the unregistered wireless device or other techniques.

According to one aspect of this disclosure, a management node configured to operate in a control plane of a wireless communication network is provided. The management node includes processing circuitry configured to: if registration of an unregistered wireless device fails, initiate collection of data associated with the unregistered wireless device; determine a virtual identifier for the unregistered wireless device based on the collected data; and initiate tracking of a spatial location of the unregistered wireless device using the virtual identifier.

In some embodiments of this aspect, the management node is configured to provide one of a plurality of network functions operating in the control plane of a wireless communication architecture of the wireless communication network. In some embodiments of this aspect, the management node is configured to

communicate with a core Access and Mobility Management Function (AMF) of a wireless communication architecture and a network node using the control plane of the wireless communication network. In some embodiments of this aspect, the processing circuitry is further configured to receive an indication that the unregistered wireless device has been detected in a cell coverage area of a network node; and receive an indication that registration of the unregistered wireless device with a network node has failed. In some embodiments of this aspect, the initiating of the collection of data includes requesting a network node to collect data associated with transmissions from the unregistered wireless device. In some embodiments of this aspect, the collected data is based on one of a radio frequency beacon from the unregistered wireless device and transmissions from the unregistered wireless device that is addressed to another wireless device. In some embodiments of this aspect, the processing circuitry is further configured to generate a plurality of signal

characteristics associated with the transmissions based on the collected data, the virtual identifier is based on the plurality of signal characteristics. In some embodiments of this aspect, the wireless device is an unmanned vehicle. In some embodiments of this aspect, the processing circuitry is further configured to transmit the virtual identifier of the unregistered wireless device to at least one other management node operating in the control plane of the wireless communication network for tracking of the unregistered wireless device in at least one cell. In some embodiments of this aspect, the processing circuitry is further configured to train a state machine using the collected data, the determination of the virtual identifier for the unregistered wireless device being based on the trained state machine.

According to another aspect of this disclosure, a method for a management node configured to operate in a control plane of a wireless communication network is provided. The method includes, if registration of an unregistered wireless device fails, initiating collection of data associated with the unregistered wireless device; generating a virtual identifier for the unregistered wireless device based on the collected data; and initiating tracking of a spatial location of the unregistered wireless device using the virtual identifier.

communicate with a core Access and Mobility Management Function (AMF) of a wireless communication architecture and a network node using the control plane of the wireless communication network. In some embodiments of this aspect, the method further includes receiving an indication that the unregistered wireless device has been detected in a cell coverage area of a network node; and receiving an indication that registration of the unregistered wireless device with a network node has failed. In some embodiments of this aspect, the initiating of the collection of data includes requesting a network node to collect data associated with transmissions from the unregistered wireless device. In some embodiments of this aspect, the collected data is based on one of a radio frequency beacon from the unregistered wireless device and transmissions from the unregistered wireless device that is addressed to another wireless device. In some embodiments of this aspect, the method includes generating a plurality of signal characteristics associated with the transmissions based on the collected data, the virtual identifier is based on the plurality of signal characteristics. In some embodiments of this aspect, the wireless device is an unmanned vehicle. In some embodiments of this aspect, the method further includes transmitting the virtual identifier of the unregistered wireless device to at least one other management node operating in the control plane of the wireless communication network for tracking of the unregistered wireless device in at least one cell. In some embodiments of this aspect, the method further includes training a state machine using the collected data, the determination of the virtual identifier for the unregistered wireless device being based on the trained state machine.

According to yet another aspect, a computer storage device storing a computer program that, when executed by at least one processor of a management node, causes the management node to perform any of the methods for the management node.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the present embodiments, and the attendant advantages and features thereof, will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings wherein:

FIG. 1 is a block diagram of example non-roaming NG reference architecture;

FIG. 2 is a schematic diagram illustrating wireless devices in a cell coverage area without communication with the cell tower;

FIG. 3 is a schematic diagram illustrating that a UTM is aware of the identity (ID) of a green drone wireless device and its location via the service provided by the operator of the cell tower and also the database of registered drones;

FIG. 4 is a schematic diagram of an example network architecture illustrating a communication system connected according to the principles in the present disclosure;

FIG. 5 is a block diagram of a network node in communication with a management node over a connection according to some embodiments of the present disclosure;

FIG. 6 is a block diagram illustrating example placement of a management node, such as, a UIMF in the reference architecture according to the principles of the present disclosure;

FIG. 7 is a flowchart of an example process in a management node for identity management according to some embodiments of the present disclosure; FIG. 8 is a flowchart of an example process in a network node for data collection according to some embodiments of the present disclosure;

FIG. 9 is a flow diagram illustrating example interactions among a network node, management node, UIMA and an unregistered wireless device according to some embodiments of the present disclosure;

FIG. 10 is a schematic diagram illustrating the establishment of an involuntary link (IL) between the network node and an unregistered wireless device in a cell coverage area according to at least some of the principles of the present disclosure;

FIG. 11 is a schematic diagram illustrating the management node utilizing data from the IL to provide a virtual identity for the unregistered wireless device, which can allow a UTM and UIMA to identify and track the unregistered wireless device according to at least some of the principles of the present disclosure;

FIG. 12 is a schematic diagram illustrating hidden and visible (collectable) data from the IL according to some embodiments of the present disclosure;

FIG. 13 is a schematic diagram illustrating state machine training using data collected from the IL according to some embodiments of the present disclosure;

FIG. 14 is a schematic diagram illustrating state machine training using data collected from the IL as well as data“generated” using a controlled green drone according to some embodiments of the present disclosure;

FIG. 15 is a schematic diagram illustrating state machine training using data collected from the IL as well as an additional fuzzy parameter according to some embodiments of the present disclosure;

FIG. 16 is a schematic diagram illustrating an example process for

determining the additional fuzzy parameter according to some embodiments of the present disclosure;

FIG. 17 is a schematic diagram illustrating state machine training using data collected from the IL as well as an additional temporal“sentence” according to some embodiments of the present disclosure;

FIG. 18 is a schematic diagram illustrating an example process for calculating the temporal sentence according to some embodiments of the present disclosure; FIG. 19 is a block diagram illustrating geographically distributed management nodes and their interactions with UIMA according to some embodiments of the present disclosure; and

FIG. 20 is a block diagram illustrating an example UTM architecture utilizing network operators associated with a wireless communication network to track unregistered UASs in cooperation with multiple actors according to at least some of the principles of the present disclosure.

DETAILED DESCRIPTION

As discussed above, converging 5^th Generation (5G) wireless standards or other wireless communication standards with Universal Traffic Management (UTM) or other protocols for unmanned/manned vehicles has not yet previously been proposed. For example, the existing business-as-usual offerings are more in the form of a denial-of-service perspective, which means that if there is no subscription to“a” carrier or a service provider, there will be no service provided (with exception of emergency calls, for example) to the wireless device. Even in the roaming use cases, there is always a carrier (a home network) in existing wireless communication standards.

This makes sense in the context of traditional wireless devices such as cellular or other mobile wireless devices, which do not have much of physical presence or potential for adverse“impact” (e.g., danger, liability, among others). In contrast, some wireless devices such as drones/UASs are wireless devices that could produce a great amount of physical impact/damage. Therefore, for some wireless devices such as drones/UASs, there may be a benefit to receiving a service (e.g., identification, tracking, among others) even if the drone/UAS is not cooperative. Providing a service for“free” may be a path for providing some channels of cooperation for wireless devices in order to indirectly receive identification/tracking services back. However, such a feature may be considered to be contrary to the subscription requirement of existing reference architectures. In other words, with the introduction of unmanned vehicles (including Drones/UASs), the current reference architectures are not ready to address and handle these new use cases, which include, for example: 1. Handling of quality of service (QoS) to a not-confined-to-two-dimensional (2D) wireless device;

2. Handling of QoS to a fast moving wireless device;

3. Handling of QoS to a not-confined-to-streets (in general, not-confined-to- any-path) wireless device; and

4. Multiple slices of connectivity with conflicting QoS requirements within a single wireless device, among others.

In many new use cases, the drone/UAS may not request a service. For example, FIG. 2 illustrates a“red drone” in a coverage area of a cell tower/network node but without communicating with the network node. Instead, there is a direct link (DL) between the red drone and a controller (e.g., remote control (RC)) of a red actor. This is illustrated in FIG. 2 in contrast with the green drone that is shown directly communicating with the network node over a direct link (DL). Thus, as used herein the term“red drone” refers to a wireless device, such as a drone, that is within a coverage area but is not communicating with a network node in that coverage area, i.e., an unregistered/unauthenticated wireless device. A“red actor” refers to the operator of a“red drone”. In some contexts a“red drone” may also be referred to as a “rogue drone”, and the operator of a rogue drone may be referred to as a“rogue actor” or a“rogue operator”. In contrast, as used herein the term“green drone” refers to a wireless device, such as a drone, that is within a coverage area and is communicating with a network node in that coverage area.

Further, FIG. 3 illustrates the identity (ID) and location of the green drone being registered with the UTM via the network node; yet an ID and location of the red drone is unknown to the UTM. Thus, the red drone/UAS may need to be forced, in some cases, to involuntarily“provide” the information in these use cases. These uses cases could have a large variety of interactions, including avoidance of a geo-defined region of interest, avoidance of a moving object (airplane), self-identification, among others.

Also, tracking of wireless devices such as drones/UASs may be a critical function for many third-party actors, including public safety actors and/or

governmental actors, and because of the costs and distributed nature, such wireless device tracking functions may not be implemented and executed without some kind of resource sharing among different actors. This feature is missing from the existing reference architectures for existing wireless communication networks. For example, different actors, including public safety actors may be involved where resource sharing (such as use of the existing cell towers and base stations) may reduce costs, especially considering the large-scale geographically-distributed nature of the drone use cases. However, such sharing is not provided by existing reference architectures.

Further, a universal function connected to global actors (such as, for example, a Universal Identity Management Authority (UIMA)) may reduce the burden on network operators in order to fulfill their responsibilities, but such functionality is not provided in existing architectures. One example use case is the case of“fly away drones” where a user loses control of a drone. These drones may fly for hundreds of kilometers, and cross the boundaries of states/provinces/countries, passing by multiple points-of-presences (PoPs) without being noticed. Unfortunately, such fly away drones can present a danger and cause physical damage.

Applicant’s disclosure provides a solution to solve at least part of the one or more problems with existing systems by modifying existing reference architecture to includes new network function(s) for handling unauthenticated/unregistered wireless devices such as drones/UASs.

With that said, some embodiments of this disclosure provide a function which may be implemented in a management node in a wireless communications network. This function may be referred to herein as a Universal Identity Management Function (UIMF), however, such function may be referred to by other names outside of this disclosure. In one embodiment, the UIMF may be added to the reference architecture in close relation with the AMF (see e.g., FIG. 6). The UIMF may provide various functions to handle the case of identification and then tracking of an uncooperative drone, which may be referred to as a“red drone”. There may be other functions outside the premises of the cell/network operators (that fall within e.g., public safety actors’ premises) that complement the UIMF functionality (see e.g., FIG. 20). The UIMF, its functions, methods, and apparatuses along with a network node (e.g., the cell tower and cell network capabilities) may sense and“virtually” identify drones (or other WDs) without requiring any direct connection between the drone and the network node. Further, a Universal Identity Management Authority (UIMA) may collect and exchange the information from/to UIMF deployments across multiple wireless network operators in order to track the drones’ movement/location using their“virtual” identities (IDs) assigned by the UIMFs. In general, the functions that the UIMA provides may include centrally (but also in a distributed manner) collecting and distributing data from all instances of UIMFs.

Advantageously, some embodiments of this disclosure provide a standard and universal method and apparatus for handling of unauthenticated/red WDs (including unauthenticated drones/UASs). Depending on the use case, application of the UIMF functions in this disclosure for authenticated WDs may also be considered.

In particular, the UIMF may provide functionalities to handle those WDs that do not authenticate (and probably are not registered anywhere). In contrast to the telecom use cases, the principles of the disclosure may address how to handle these unregistered WDs because they may impose a physical danger. The UIMF allows for tracking of these WDs (and, in some embodiments, also registered WDs) with or without collaboration from the WD itself.

Some embodiments of this disclosure advantageously provide a new reference architecture for handling use cases that do not currently exist.

In the past, having a traffic management for drones/UASs was not considered in any architecture because there was no forecast of such a need. In contrast, the Federal Aviation Administration (FAA), the Federal Communications Commission (FCC), and the National Aeronautics and Space Administration (NASA) in collaboration with many vendors and operators are now considering universal UAS Traffic Management (UTM).

In the future, there may be even more physically-enabled, less-restricted, and more powerful“things’VWDs introduced into society and the environment that should be managed and handled, with or without registration and/or authentication to a network.

Some embodiments of this disclosure provide methods and apparatuses for large scale (in space and time) govemance/tracking of wireless devices such as drones/UASs using 5G resources, without requiring a large amount of additional resource allocation and investment. Some embodiments of this disclosure provide a roadmap and integration of a UTM in the 5G solution in the future, which accelerates such integration and at the same time makes 5G an element of UTMs.

Some revenue advantages associated with the principles in this disclosure could include opening a standardized approach to commercialization of drone/UAS applications. It is possible identifying/tracking drones may become a requirement by the government (enforced). Therefore, a standard approach according to the principles of this disclosure could reduce the burden on the telecom operators. Furthermore, customers (e.g., drone operators) may benefit from increased commercialization of drone/UAS applications. Also, customers (e.g., general public) may benefit from a lower rate of abusive cases of using drones.

Before describing in detail example embodiments, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to providing reference architecture for WD (e.g., red drone) identification and/or tracking. Accordingly, components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein. Like numbers refer to like elements throughout the description.

As used herein, relational terms, such as“first” and“second,”“top” and “bottom,” and the like, may be used solely to distinguish one entity or element from another entity or element without necessarily requiring or implying any physical or logical relationship or order between such entities or elements. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the concepts described herein. As used herein, the singular forms“a”,“an” and“the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,”“comprising,”“includes” and/or“including” when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. In embodiments described herein, the joining term,“in communication with” and the like, may be used to indicate electrical or data communication, which may be accomplished by physical contact, induction, electromagnetic radiation, radio signaling, infrared signaling or optical signaling, for example. One having ordinary skill in the art will appreciate that multiple components may interoperate and modifications and variations are possible of achieving the electrical and data communication.

In some embodiments described herein, the term“coupled,”“connected,” and the like, may be used herein to indicate a connection, although not necessarily directly, and may include wired and/or wireless connections.

The term“network node” used herein can be any kind of network node comprised in a radio network which may further comprise any of base station (BS), radio base station, base transceiver station (BTS), base station controller (BSC), radio network controller (RNC), g Node B (gNB), evolved Node B (eNB or eNodeB), Node B, multi-standard radio (MSR) radio node such as MSR BS, multi-cell/multicast coordination entity (MCE), relay node, donor node controlling relay, radio access point (AP), transmission points, transmission nodes, Remote Radio Unit (RRU) Remote Radio Head (RRH), a core network node (e.g., mobile management entity (MME), self-organizing network (SON) node, a coordinating node, positioning node, MDT node, etc.), an external node (e.g., 3rd party node, a node external to the current network), nodes in distributed antenna system (DAS), a spectrum access system (SAS) node, an element management system (EMS), etc. The network node may also comprise test equipment. The term“radio node” used herein may be used to also denote a wireless device (WD) such as a wireless device (WD) or a radio network node.

In some embodiments, the non-limiting terms wireless device (WD) or a user equipment (UE) are used interchangeably. The WD herein can be any type of wireless device capable of communicating with a network node or another WD over radio signals, such as wireless device (WD), a UAS, a UAV, or a drone. The WD may also be a radio communication device, target device, device to device (D2D) WD, machine type WD or WD capable of machine to machine communication (M2M), low-cost and/or low-complexity WD, a sensor equipped with WD, Tablet, mobile terminals, smart phone, laptop embedded equipped (LEE), laptop mounted equipment (LME), USB dongles, Customer Premises Equipment (CPE), an Internet of Things (IoT) device, or a Narrowband IoT (NB-IOT) device, etc. In some embodiments, the WD may be a drone or UAS.

Also, in some embodiments the generic term“radio network node” is used. It can be any kind of a radio network node which may comprise any of base station, radio base station, base transceiver station, base station controller, network controller, RNC, evolved Node B (eNB), Node B, gNB, Multi-cell/multicast Coordination Entity (MCE), relay node, access point, radio access point, Remote Radio Unit (RRU) Remote Radio Head (RRH).

In some embodiments, the terms“virtual identifier” and“virtual identity” and “virtual ID” are used interchangeably. In some embodiments, the virtual ID may be based on a plurality of unique or distinguishable signal characteristics (e.g., radio frequency (RF) transmission characteristics or optical transmissions, etc.) associated with a WD. In some embodiments, the virtual ID may be a UAV RF fingerprint based on spectral analysis. In some embodiments, the virtual ID may be obtained from a beacon signal from the WD (e.g., collision avoidance signals). In some embodiments, the virtual ID may be based on other identifying characteristics of the WD. In some embodiments, the virtual ID may be considered to uniquely identify the WD. In other embodiments, the virtual ID may not be globally unique, but be sufficiently distinct for tracking a WD across one or more cells over a reasonable or useful time period.

Note that although terminology from one particular wireless system, such as, for example, 3GPP LTE, 5G and/or New Radio (NR), may be used in this disclosure, this should not be seen as limiting the scope of the disclosure to only the

aforementioned system. Other wireless systems, including without limitation Wide Band Code Division Multiple Access (WCDMA), Worldwide Interoperability for Microwave Access (WiMax), Ultra Mobile Broadband (UMB) and Global System for Mobile Communications (GSM), may also benefit from exploiting the ideas covered within this disclosure.

Note further, that functions described herein as being performed by a management node or a network node may be distributed over a plurality of management nodes and/or network nodes. In other words, it is contemplated that the functions of the network node and management node described herein are not limited to performance by a single physical device and, in fact, can be distributed among several physical devices. Similarly, it is contemplated that the functions performed by the management node and by the network node can be implemented together in a single physical node.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning that is consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

Returning to the drawing figures, in which like elements are referred to by like reference numerals, there is shown in FIG. 4 a schematic diagram of a communication system 10, according to an embodiment, such as a 3GPP-type cellular network that may support standards such as LTE, 5G and/or NR (5G), which comprises an access network 12, such as a radio access network, and a core network 14. The access network 12 comprises a plurality of network nodes l6a, l6b, l6c (referred to collectively as network nodes 16), such as NBs, eNBs, gNBs or other types of wireless access points, each defining a corresponding coverage area l8a, l8b, l8c (referred to collectively as coverage areas 18). Each network node l6a, l6b, l6c is connectable to the core network 14 over a wired and/or wireless connection 20. A first wireless device (WD) 22a, which may be a UAS, is located in coverage area l8a served by the corresponding network node l6c. A second WD 22b is in coverage area l8b and is configured to wirelessly connect to, or be paged by, the corresponding network node l6a. While a plurality of WDs 22a, 22b (collectively referred to as wireless devices 22) are illustrated in this example, the disclosed embodiments are equally applicable to a situation where a sole WD is in the coverage area or where a sole WD is connecting to the corresponding network node 16. The system 10 may also include a plurality of management nodes 23a, 23b, 23c, 23d, which may be associated with corresponding network nodes l6a, l6b, l6c. The management nodes 23a, 23b, 23b, 23d (collectively referred to as management node 23) may be configured to facilitate identifying and/or tracking unregistered WDs 22 traveling through the corresponding coverage areas l8a, l8b, l8c, respectively, according to at least some of the principles of this disclosure. In some embodiments, the

management node 23 may also be configured to identify and/or track registered WDs 22, as well. Note that although only two WDs 22, four management nodes 23 and three network nodes 16 are shown for convenience, the communication system 10 may include many more WDs 22, management nodes 23 and network nodes 16.

Also, it is contemplated that a WD 22 can be in simultaneous communication and/or configured to separately communicate with more than network node 16 and more than one type of network node 16. For example, a WD 22 can have dual connectivity with a network node 16 that supports LTE and the same or a different network node 16 that supports NR. As an example, the WD 22 can be in

communication with an eNB for LTE/E-UTRAN and a gNB for NR/NG-RAN.

In one embodiment of the present disclosure, a network node 16 is configured to include a data collection unit 32 which is configured to detect an unregistered WD 22 in a cell coverage area 18 and determine whether registration of the WD 22 failed. The data collection unit 32 may cause the network node 16 to transmit an indication that registration of the unregistered WD 22 failed, report collected data associated with the unregistered WD 22, and monitor the unregistered WD 22 using a virtual identity, the virtual identity being based on the collected data.

In one embodiment of the present disclosure, a management node 23 is configured to include an identity management unit 34 which is configured to, if registration of an unregistered wireless device 22 fails, initiate collection of data associated with the unregistered wireless device 22; determine a virtual identifier for the unregistered wireless device 22 based on the collected data; and initiate tracking of a spatial location of the unregistered wireless device 22 using the virtual identifier.

Example implementations, in accordance with an embodiment, of the WD 22 and network node 16 discussed in the preceding paragraphs will now be described with reference to FIG. 5. In a communication system 10, a network node 16 comprises hardware 40 enabling it to communicate with the WD 22 and/or the management node 23 via a connection 42. In some embodiments, control plane communications may be performed over the connection 42 between the network node 16 and the management node 23 according to the principles of this disclosure. The hardware 40 may include a communication interface 44. The communication interface 44 may be configured for setting up and maintaining a wired connection with an interface of a different communication device of the communication system 10. The communication interface 44 may include a radio interface for setting up and maintaining at least a wireless connection with a WD 22 located in a coverage area 18 served by the network node 16. The radio interface may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and/or one or more RF transceivers.

In the embodiment shown, the hardware 40 of the network node 16 further includes processing circuitry 46. The processing circuitry 46 may include a processor 48 and a memory 50. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 46 may comprise integrated circuitry for processing and/or control, e.g., one or more processors and/or processor cores and/or FPGAs (Field Programmable Gate Array) and/or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 48 may be configured to access (e.g., write to and/or read from) the memory 50, which may comprise any kind of volatile and/or nonvolatile memory, e.g., cache and/or buffer memory and/or RAM (Random Access Memory) and/or ROM (Read-Only Memory) and/or optical memory and/or EPROM (Erasable Programmable Read-Only Memory).

Thus, the network node 16 further has software 52 stored internally in, for example, memory 50, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the network node 16 via an external connection. The software 52 may be executable by the processing circuitry 46. The processing circuitry 46 may be configured to control any of the methods and/or processes described herein and/or to cause such methods, and/or processes to be performed, e.g., by network node 16. Processor 48 corresponds to one or more processors 48 for performing network node 16 functions described herein. The memory 50 is configured to store data, programmatic software code and/or other information described herein. In some embodiments, the software 52 may include instructions that, when executed by the processor 48 and/or processing circuitry 46, causes the processor 48 and/or processing circuitry 46 to perform the processes described herein with respect to network node 16. For example, processing circuitry 46 of the network node 16 may include the data collection unit 32 configured to configured to detect an unregistered WD 22 in a cell coverage area 18 and determine whether registration of the WD 22 failed. The data collection unit 32 may cause the network node 16 to transmit an indication that registration of the unregistered WD 22 failed, report collected data associated with the unregistered WD 22, and monitor the unregistered WD 22 using a virtual identity, the virtual identity being based on the collected data.

The communication system 10 further includes the management node 23 already referred to. The management node 23 may have hardware 60 that may include a communication interface 62. The communication interface 62 may be configured to set up and maintain a connection 42 with a network node 16. In some embodiments, control plane communications may be performed over the connection 42 between the network node 16 and the management node 23 according to the principles of this disclosure. The communication interface 62 may be configured for setting up and maintaining a wired connection with an interface of a different communication device of the communication system 10. The communication interface 62 may include a radio interface that may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and/or one or more RF transceivers.

The hardware 60 of the management node 23 further includes processing circuitry 64. The processing circuitry 64 may include a processor 66 and memory 68. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 64 may comprise integrated circuitry for processing and/or control, e.g., one or more processors and/or processor cores and/or FPGAs (Field Programmable Gate Array) and/or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 66 may be configured to access (e.g., write to and/or read from) memory 68, which may comprise any kind of volatile and/or nonvolatile memory, e.g., cache and/or buffer memory and/or RAM (Random Access Memory) and/or ROM (Read-Only Memory) and/or optical memory and/or EPROM (Erasable Programmable Read-Only

Memory). Thus, the management node 23 may further comprise software 70, which is stored in, for example, memory 68 at the management node 23, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the management node 23. The software 70 may be executable by the processing circuitry 64. The processing circuitry 64 may be configured to control any of the methods and/or processes described herein and/or to cause such methods, and/or processes to be performed, e.g., by management node 23. The processor 66 corresponds to one or more processors 66 for performing management node 23 functions described herein. The management node 23 includes memory 68 that is configured to store data, programmatic software code and/or other information described herein. In some embodiments, the software 70 may include instructions that, when executed by the processor 66 and/or processing circuitry 64, causes the processor 66 and/or processing circuitry 64 to perform the processes described herein with respect to management node 23. For example, the processing circuitry 64 of the wireless device 22 may include an identity management unit 34 configured to, if registration of an

unregistered wireless device 22 fails, initiate collection of data associated with the unregistered wireless device 22; determine a virtual identifier for the unregistered wireless device 22 based on the collected data; and initiate tracking of a spatial location of the unregistered wireless device 22 using the virtual identifier.

In some embodiments, the management node 23 is configured to provide one of a plurality of network functions operating in the control plane of a wireless communication architecture of the wireless communication network. In some embodiments, the management node 23 is configured to communicate with a core Access and Mobility Management Function (AMF) of a wireless communication architecture and a network node 16 using the control plane of the wireless

communication network. In some embodiments, the processing circuitry 64 is further configured to receive an indication that the unregistered wireless device 22 has been detected in a cell coverage area 18 of a network node 16; and receive an indication that registration of the unregistered wireless device 22 with a network node 16 has failed. In some embodiments, the initiating of the collection of data includes requesting a network node 16 to collect data associated with transmissions from the unregistered wireless device 22. In some embodiments, the collected data is based on one of a radio frequency beacon (e.g., Automatic Dependent Surveillance - Broadcast (ADS-B) system) from the unregistered wireless device 22 and transmissions from the unregistered wireless device 22 that is addressed to another wireless device 22 (e.g., collision avoidance signal). In some embodiments, the processing circuitry 64 is further configured to generate a plurality of signal characteristics associated with the transmissions based on the collected data, the virtual identifier is based on the plurality of signal characteristics. In some embodiments, the wireless device 22 is an unmanned vehicle. In some embodiments, the processing circuitry 64 is further configured to transmit the virtual identifier of the unregistered wireless device 22 to at least one other management node 23 operating in the control plane of the wireless communication network for tracking of the unregistered wireless device 22 in at least one cell. In some embodiments, the processing circuitry 64 is further configured to train a state machine using the collected data, the determination of the virtual identifier for the unregistered wireless device 22 being based on the trained state machine.

In some embodiments, the inner workings of the network node 16 and management node 23 may be as shown in FIG. 5 and independently, the surrounding network topology may be that of FIG. 4.

In FIG. 5, a connection 42 between the management node 23 and the network node 16 is shown, which may include a wired and/or wireless connection, in accordance with the teachings of the embodiments described throughout this disclosure.

Although FIGS. 4 and 5 illustrate the network node 16 and the management node 23 being separate, it is contemplated that, in some embodiments, the network node 16 and the management node 23 may be implemented in the same node or device. In other words, in some embodiments, the functions of the network node 16 and the management node 23 discussed herein may be implemented in the same node.

Although FIGS. 4 and 5 show various“units” such as the data collection unit 32, and identity management unit 34 as being within a respective processor, it is contemplated that these units may be implemented such that a portion of the unit is stored in a corresponding memory within the processing circuitry. In other words, the units may be implemented in hardware or in a combination of hardware and software within the processing circuitry.

FIG. 6 illustrates example placement of a management node 23, such as, a Universal Identity Management Function (UIMF) in a reference architecture according to the principles of the present disclosure. The management node 23 may be connected to the AMF and the network node 16, which may communicate with one another using, for example a control plane of the wireless communication network.

As can be seen in a comparison of FIG. 1 with FIG. 6, a UDM-Universal Identity Management (UIM) may also be placed in the reference architecture in

communication with the management node 23. The management node 23 may include the UIMF and, in some embodiments, the UIMF may be co-located with the AMF.

FIG. 7 is a flowchart of an example process in a management node 23 configured to operate in a control plane of a wireless communication network. The method includes, if registration of an unregistered wireless device 22 fails, initiating collection of data associated with the unregistered wireless device 22 (block S100). The method includes generating a virtual identifier for the unregistered wireless device 22 based on the collected data (block S102). The method includes initiating tracking of a spatial location of the unregistered wireless device 22 using the virtual identifier (block S104). In some embodiments, the management node 23 is configured to provide one of a plurality of network functions operating in the control plane of a wireless communication architecture of the wireless communication network. In some embodiments, the management node 23 is configured to

communicate with a core Access and Mobility Management Function (AMF) of a wireless communication architecture and a network node 16 using the control plane of the wireless communication network. In some embodiments, the method includes receiving an indication that the unregistered wireless device 22 has been detected in a cell coverage area 18 of a network node 16; and receiving an indication that registration of the unregistered wireless device 22 with a network node 16 has failed.

In some embodiments, the initiating of the collection of data includes requesting a network node 16 to collect data associated with transmissions from the unregistered wireless device 22. In some embodiments, the collected data is based on one of a radio frequency beacon from the unregistered wireless device 22 and transmissions from the unregistered wireless device 22 that is addressed to another wireless device 22. In some embodiments, the method further includes generating a plurality of signal characteristics associated with the transmissions based on the collected data, the virtual identifier is based on the plurality of signal characteristics. In some embodiments, the wireless device 22 is an unmanned vehicle. In some embodiments, the method further includes transmitting the virtual identifier of the unregistered wireless device 22 to at least one other management node 23 operating in the control plane of the wireless communication network for tracking of the unregistered wireless device 22 in at least one cell. In some embodiments, the method further includes training a state machine using the collected data, the determination of the virtual identifier for the unregistered wireless device 22 being based on the trained state machine.

FIG. 8 is a flowchart of an example process in a network node 16 according to some embodiments of the present disclosure. The process may include the network node 16 detecting an unregistered wireless device 22 in a cell coverage area 18 (block S 106). The process may include determining whether registration of the wireless device 22 failed (block S 108). If the registration is successful, the process may return S106 where the network node 16 continues to detect unregistered wireless devices 22 in the cell coverage area 18. On the other hand, if the registration failed, the network node 16 may transmit an indication that registration of the unregistered wireless device 22 failed (block S 110). In some embodiments, such transmission may be to the management node 23. The network node 16 may report collected data associated with the unregistered wireless device 22 (block S 112). In some embodiments, the report may be sent to the management node 23. The network node 16 may monitor the unregistered wireless device 22 using a virtual identity, the virtual identity being based on the collected data (block S 114). In some embodiments, the network node 16 may receive this virtual identity from the management node 23.

Having described some embodiments of this disclosure for providing reference architecture in a wireless communication network that can identify and/or track an unregistered WD 22, a more detailed description of example implementations of some of the embodiments will be described below, with reference to FIGS. 9-20. FIG. 9 is a flow diagram illustrating an example process for identifying and tracking an unregistered WD 22 such as a drone/UAS according to the present disclosure. The process may include communications and/or interactions between the network node 16, a radio associated with the network node 16, the management node 23, the WD 22 and the UIMA. In one embodiment, the UIMF may be collocated with the AMF in the management node 23. In one embodiment, the management node 23 may be located at the cell tower. The network node 16 (e.g., eNB) may be in constant contact with the management node 23 (e.g., UIMF) in order to detect the presence of a drone in the cell coverage area 18. For example, in step S120, the network node 16 may continuously or periodically monitor the radio to detect unregistered WDs 22.

In step S122, the WD 22 enters the cell tower coverage and the radio may detect transmissions associated with the WD 22. In one embodiment, the

transmissions may be radio transmissions from the WD 22, such as, for example active transmissions or even passive reflection/deflection or other spectral

characteristics of a transceiver at the WD 22. In another embodiment, the

transmissions may be radio transmissions from a radio frequency beacon at the WD 22. In some embodiments, the transmissions may be optical transmissions. In yet other embodiments, the transmissions associated with the WD 22 may be any feature from the WD 22 that is detectable by the radio and/or the network node 16. In the case of presence of a drone/WD 22, and if the drone/WD 22 is of interest, the management node 23 may start the process of identifying the red drone. For example, in step S124, the radio may report the detection of the drone/WD 22 to the network node 16 and, in step S126, the network node 16 may activate the management node 23 (e.g., via a control plane message from the network node 16 to the management node 23).

In step S128, the management node 23 may send a message to the network node 16 to request“collected data” X of an instance. In step S130, responsive to the request, the network node 16 may approve and execute the request for collected data X. The radio may then establish an involuntary link (IL) with the unregistered WD 22 and collect the data associated with the WD 22 in step S132.

FIG. 10 illustrates the establishment of an IL between the unregistered WD 22 (i.e., red drone) and the radio of the network node 16. Returning to FIG. 9, the radio may report the collected data X to the network node 16 in step S134. In step S136, the network node 16 may compile the collected data X and then send the

compiled/collected data to the management node 23. The management node 23 may perform an initial analysis of the collected data and generate and train a state machine using the collected data in step S138. The management node 23 may generate a virtual identifier (ID) based on the collected data and/or the trained state machine.

The final outcome of the training (e.g., the state machine’s configuration/parameters) may be considered as the“virtual” ID of the WD 22. In some embodiments, the virtual identifier may be a kind of bio-metrics for the particular WD 22 that is not generally cloneable. For example, the virtual identifier may be based on a plurality of unique or distinguishable signal characteristics (e.g., radio frequency (RF) fingerprints based on variations or imperfections in the analog components of a radio transmitter at the WD 22) that may be caused by radio wave transmissions from hardware in the WD 22. In other embodiments, the virtual identifier may be based on other identifying characteristics of the WD 22. Various techniques for analyzing collected data, training the state machine, and generating the virtual identifier according to one embodiment of the present disclosure are discussed in more detail below with respect to FIGS. 12-18.

In some embodiments, instead of building a virtual ID based on collected data and training a state machine, the virtual ID may be obtained in other ways. For example, the management node 23 may obtain a virtual ID from an Automatic Dependent Surveillance - Broadcast (ADS-B) system on the WD 22, or a wireless protocol for UAVs, where the unregistered WD 22 would transmit its ID to another device (e.g., collision avoidance signals). Thus, in some embodiments, the management node 23 may obtain the ID by reading the ID or looking-up the ID by for example a network lookup. The management node 23 may, for example, actively cause the unregistered WD 22 to transmit an ID or some other identifying signal, or the management node 23 may passively detect an ID or some other identifying signal transmitted by the WD 22.

When the management node 23 builds or obtains the“virtual” ID associated with the WD 22 (e.g., the state machine configuration/parameters of the associated state machine), the management node 23 may exchange the“virtual” ID with other management nodes 23 and/or the UIMA. The exchange may be performed systematically via the UIMA that also handles the exchange with various public safety actors, among other officials/bodies (e.g., see FIG. 20). In step S140, the

management node 23 may report the state machine to the UIMA and request records associated with this virtual ID at the UIMA. In step S142, the UIMA may

acknowledge the request and record the virtual ID and location of the unregistered WD 22 in step S142. The UIMA may also send additional commands related to tracking the unregistered WD 22. FIG. 11 illustrates the virtual ID and location of the unregistered WD 22 (i.e., red drone) being known to the UTM via the principles of this disclosure.

Referring again to FIG. 9, the tracking of the spatial location and also spectral behavior of the unregistered WD 22 could be continued depending on the interest of the UIMA and other authorities. In step S144, the management node 23 may send a message to the network node 16 related to the unregistered WD 22 based, for example, on the commands from the UIMA. The message could be a request to continue monitoring the unregistered WD 22 associated with the virtual ID.

Alternatively, the message could be a request message to discontinue monitoring, or to not monitor the particular WD 22. In some embodiments, the management node 23 may transmit the virtual identifier of the unregistered WD 22 to at least one other management node 23 operating in the control plane of the wireless communication network for tracking of the unregistered WD 22 across one or even multiple cells.

Having described one example process for identifying and tracking a WD 22 according to the principles of this disclosure, at least some example techniques for analyzing the collected data X, training the state machine using the collected data A, and generating the virtual identifier according to some embodiments of this disclosure are discussed with reference to FIGS. 12-18.

According to another example method of this disclosure, a request for “collected data” X of an instance (e.g., an encounter with a drone WD 22) is sent by e.g., the management node 23. The management node 23 (e.g., UIMF) receives an instance from the AMF or the network node 16. The management node 23 (or UIMA) may determine that the instance is an instance-of-interest. The management node 23 (e.g., UIMF) may send a request to the AMF or network node 16 for “collected data” X. In some embodiments, the data X may be a series of data points associated with signal characteristics of the WD 22. Each data point may describe or represent the spectral features of the WD 22 observed by the network node 16 (e.g., eNodeB/(R)AN), as shown for example in FIG. 12. The data points may include but are not limited to: mean frequency (k_mean), min frequency (k_min), max frequency (k_max), power at mean frequency (Pimean), power at min frequency (Pimin), and power at max frequency (Pimax) (see FIG. 13). The values for these data points may be derived from the raw collected data (e.g., in steps S134 and S136 of FIG. 9) over the time period associated to that data point, e.g., from t_n to t_(n+l). In some embodiments, the min/max are calculated using a percentage threshold (for example, 5%/95%) imposed on the distribution of data (e.g., the power spectrum) over the time interval.

In one embodiment, a state machine may be trained on X to get the“virtual” ID, as shown, for example in FIG. 13. The state machine training may be performed for example, by the management node 23 in step S138 of FIG. 9. The data points may be used to train a state machine to obtain the virtual ID, which may be sent to the UIMA e.g., in step S140 of FIG. 9. In one embodiment, an initialized machine is used. If the initialized machine is used (for example, when a trained machine from a green drone is used as the initial machine), the configuration/parameters of the state machine are initially set to those of the given machine. In an alternative embodiment (without an initialized machine), hyper-parameters of the machine may be provided (the number of states, for example). A template state machine can be generated based on the hyper-parameters, and then the parameters may be set randomly, considering best practices known. In yet another embodiment, default hyper-parameters (for example, the number of states equal to a predetermined number, such as five (5)) may be used. A template state machine may be generated based on those hyper

parameters, and then parameters may be set randomly, considering best known practices.

In some embodiments, the whole X series of data points may be used to train the state machine, or a set of sub-series sampled from X may be used. The

subsampled X series may be continuous within themselves, i.e., the data points of each of them may have the same index in the original X series. For each of the series (which may be only one series if the whole X series is used), the following optimization problems may be solved:

1. Maximize (by modifying the parameters of the machine) the transition probabilities, the starting probabilities for each state, the parameters of the emission distribution for each state, the parameters and type of sojourn distribution for each state, among others. Maximize the probability of having the predicted observation from the machine matching that of the actual observations X.

a. Algorithms such as Viterbi Algorithm and the Expectation- Maximization (EM) Algorithm can be used to find the optimal state sequences and also the optimal parameter values of this

optimization problem.

b. mhsmm (Inference for Hidden Markov and Semi-Markov Models) for example is an R language package that can be used for the purpose of solving the optimization problem.

In other embodiments, yet other statistical algorithms and known techniques may be used to train the state machine. Techniques for training a state machine are known and will therefore not be discussed in great detail herein.

If there is more than one training series, the trained machine for each series may be combined into a single machine, for example using a‘mean’ method. In one embodiment, the trained state machine may be returned (i.e., the set of hyper parameters and the parameters of the machine optimized, as in the processes described above) as the“virtual” ID of the WD 22.

FIG. 13 illustrates that the collected data X is fed into a training process to build a“state machine” associated to the source of that data. The state machine then can predict the state of the source (S). Hidden Markov Machines (hmm) or Hidden Semi-Markov Machines (hsmm) are the basic choices for the state machine; however, this disclosure is not limited to them, as other known techniques for the state machine may be used. The training of the state machine can be: 1) unsupervised (e.g., only relying on the collected data), or 2) initiated from a supervised-trained machine then fine-tuned with the collected data. FIG. 14 is a schematic diagram illustrating a mechanism to train a state machine using the data from a“green drone” in a supervised manner. The collected data (X) is not accompanied with the true technology type used for the

communications (T). The state machine is then trained using both these data sets. The generating of an (X, T) tuple could be with a predefined scenario (e.g., when and to what technology it switches), or by observing a dgreen drone while performing other operations (e.g., unplanned sequences).

FIG. 15 illustrates that, in addition to the basic data, another field may be added to the basic data set, for example, a Pfuzzy field. Pfuzzy may be considered a numeric (or other) representation of the whole spectrum power profile. FIG. 16 illustrates details for how the Pfuzzy may be calculated. For example, to calculate the Pfuzzy, for every observed power spectrum profile within a time interval t_(n, n-l), i.e., from t_(n-l) to t_n, the distance between that profile and those in a fuzzy dictionary may be calculated and then based on a threshold (or other measures) a match is decided. If there is no match, the profile is added to the dictionary. An L2 Norm is shown as a measure of distance, however other norms can also be used. The collected data (X) with the additional Pfuzzy parameter may be considered an extended X, which is the basic X augmented with the“Pfuzzy” representation of the power spectrum. In some embodiments, the Pfuzzy could be an“index” from the dictionary of the“Pfuzzy” representations.

In another embodiment, an extended X could include the basic X augmented with temporal“sentence” representations of the signal over the involuntary link (IL), as shown in FIG. 17. The“sentence” is a numeric (or other) representation of temporal behavior of the radio frequency (RF) signal on the IL. FIG. 18 illustrates some of the details for the calculations of the sentence. To calculate the“sentence”, the“temporal power spectrum profile” is calculated. The temporal profile is a locally averaged profile with a time averaging window of much less than the actual t_(n, n-l) time interval. A dictionary of“sentences” may be provided. Any new temporal profile is matched against the dictionary (using thresholding or any other method). If there is a match, the index of the matching sentence in the dictionary is used as the“sentence” feature in X. In other words, the temporal“sentence” could be an index from the dictionary of the“sentence” representations If there is not a match, the new temporal profile is added to the dictionary as a new dictionary sentence.

FIG. 19 is a block diagram illustrating geographically distributed UDM-UIMA instances and their interactions with UDM-UIM instances and their corresponding management nodes 23 (e.g., UIMF instances). Accordingly, the virtual IDs for unregistered WDs 22 can be communicated to and/or managed by the UIMA for e.g., tracking the movement of the unregistered WDs 22 across the network over multiple cell coverage areas 18 via multiple geographically distributed cell towers.

FIG. 20 illustrates an example UTM architecture including infrastructure from multiple third-party actors, such as, for example the FAA and public safety actors. For example, the USS entities shown in the diagram can be the telecom operators associated with the new reference architecture discussed in this disclosure.

Accordingly, this disclosure provides for a new function, which may be implemented in a management node in a wireless communications network. The management node (e.g., UIMF) may be added to the reference architecture in close relation with the AMF. The management node may provide various functions to handle the case of identification and then tracking of an uncooperative WD (e.g., red drone) moving through cell coverage areas. The management node may facilitate sensing and“virtually” identifying drones (or other WDs) without requiring any direct connection between the drone and the network node. Further, a Universal Identity Management Authority (UIMA) may collect and exchange the information from/to instances of management nodes across multiple wireless network operators in order to track the drones’ movement/location using their“virtual” identities (IDs) assigned by the management nodes.

Any two or more embodiments described in this disclosure may be combined in any way with each other.

As will be appreciated by one of skill in the art, the concepts described herein may be embodied as a method, data processing system, and/or computer program product. Accordingly, the concepts described herein may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects all generally referred to herein as a “circuit” or“module.” Furthermore, the disclosure may take the form of a computer program product on a tangible computer usable storage medium having computer program code embodied in the medium that can be executed by a computer. Any suitable tangible computer readable medium may be utilized including hard disks, CD-ROMs, electronic storage devices, optical storage devices, or magnetic storage devices.

Some embodiments are described herein with reference to flowchart illustrations and/or block diagrams of methods, systems and computer program products. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer readable memory or storage medium that can direct a computer or other

programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

It is to be understood that the functions/acts noted in the blocks may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Although some of the diagrams include arrows on communication paths to show a primary direction of communication, it is to be understood that

communication may occur in the opposite direction to the depicted arrows.

Computer program code for carrying out operations of the concepts described herein may be written in an object oriented programming language such as Java® or C++. However, the computer program code for carrying out operations of the disclosure may also be written in conventional procedural programming languages, such as the "C" programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer. In the latter scenario, the remote computer may be connected to the user's computer through a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

Many different embodiments have been disclosed herein, in connection with the above description and the drawings. It will be understood that it would be unduly repetitious and obfuscating to literally describe and illustrate every combination and subcombination of these embodiments. Accordingly, all embodiments can be combined in any way and/or combination, and the present specification, including the drawings, shall be construed to constitute a complete written description of all combinations and subcombinations of the embodiments described herein, and of the manner and process of making and using them, and shall support claims to any such combination or subcombination.

Abbreviations that may be used in the preceding description include:

Abbreviation Explanation

UIMA Universal Identity Management Authority

UBMGF Universal Biometrics Generation Function

DRBM Device Radio and Behavior Metrics

InHF Instance Handling Function

DMF Data Management Function

UUE Unauthenticated UE

AUE Authenticated UE PoD Point of Decision

CPS Cyber-Physical System

IL Involuntary Link

IoT Internet of Things

UAV Unmanned Aerial Vehicle

UAS Unmanned Aircraft System

Drone A UAV or UAS

It will be appreciated by persons skilled in the art that the embodiments described herein are not limited to what has been particularly shown and described herein above. In addition, unless mention was made above to the contrary, it should be noted that all of the accompanying drawings are not to scale. A variety of modifications and variations are possible in light of the above teachings without departing from the scope of the following claims.

Claims

What is claimed is:

1. A management node (23) configured to operate in a control plane of a wireless communication network, the management node (23) including:

processing circuitry (64) configured to:

if registration of an unregistered wireless device (22) fails, initiate collection of data associated with the unregistered wireless device (22);

determine a virtual identifier for the unregistered wireless device (22) based on the collected data; and

initiate tracking of a spatial location of the unregistered wireless device (22) using the virtual identifier.

2. The management node (23) of Claim 1, wherein the management node (23) is configured to provide one of a plurality of network functions operating in the control plane of a wireless communication architecture of the wireless communication network.

3. The management node (23) of any one of Claims 1-2, wherein the management node (23) is configured to communicate with a core Access and Mobility Management Function (AMF) of a wireless communication architecture and a network node (16) using the control plane of the wireless communication network.

4. The management node (23) of any one of Claims 1-3, wherein the processing circuitry (64) is further configured to:

receive an indication that the unregistered wireless device (22) has been detected in a cell coverage area (18) of a network node (16); and

receive an indication that registration of the unregistered wireless device (22) with a network node (16) has failed.

5. The management node (23) of any one of Claims 1-4, wherein the initiating of the collection of data includes requesting a network node (16) to collect data associated with transmissions from the unregistered wireless device (22).

6. The management node (23) of any one of Claims 1-5, wherein the collected data is based on one of a radio frequency beacon from the unregistered wireless device (22) and transmissions from the unregistered wireless device (22) that is addressed to another wireless device (22).

7. The management node (23) of any one of Claims 1-6, wherein the processing circuitry (64) is further configured to generate a plurality of signal characteristics associated with the transmissions based on the collected data, the virtual identifier is based on the plurality of signal characteristics.

8. The management node (23) of any one of Claims 1-7, wherein the wireless device (22) is an unmanned vehicle.

9. The management node (23) of any one of Claims 1-8, wherein the processing circuitry (64) is further configured to transmit the virtual identifier of the unregistered wireless device (22) to at least one other management node (23) operating in the control plane of the wireless communication network for tracking of the unregistered wireless device (22) in at least one cell.

10. The management node (23) of any one of Claims 1-9, wherein the processing circuitry (64) is further configured to:

train a state machine using the collected data, the determination of the virtual identifier for the unregistered wireless device (22) being based on the trained state machine.

11. A method for a management node (23) configured to operate in a control plane of a wireless communication network, the method comprising:

if registration of an unregistered wireless device (22) fails, initiating (S100) collection of data associated with the unregistered wireless device (22);

generating (S102) a virtual identifier for the unregistered wireless device (22) based on the collected data; and initiating (S104) tracking of a spatial location of the unregistered wireless device (22) using the virtual identifier.

12. The method of Claim 11, wherein the management node (23) is configured to provide one of a plurality of network functions operating in the control plane of a wireless communication architecture of the wireless communication network.

13. The method of any one of Claims 11-12, wherein the management node (23) is configured to communicate with a core Access and Mobility

Management Function (AMF) of a wireless communication architecture and a network node (16) using the control plane of the wireless communication network.

14. The method of any one of Claims 11-13, further comprising:

receiving an indication that the unregistered wireless device (22) has been detected in a cell coverage area (18) of a network node (16); and

receiving an indication that registration of the unregistered wireless device (22) with a network node (16) has failed.

15. The method of any one of Claims 11-14, wherein the initiating of the collection of data includes requesting a network node (16) to collect data associated with transmissions from the unregistered wireless device (22).

16. The method of any one of Claims 11-15, wherein the collected data is based on one of a radio frequency beacon from the unregistered wireless device (22) and transmissions from the unregistered wireless device (22) that is addressed to another wireless device (22).

17. The method of any one of Claims 11-16, further comprising generating a plurality of signal characteristics associated with the transmissions based on the collected data, the virtual identifier is based on the plurality of signal characteristics.

18. The method of any one of Claims 11-17, wherein the wireless device (22) is an unmanned vehicle.

19. The method of any one of Claims 11-18, further comprising transmitting the virtual identifier of the unregistered wireless device (22) to at least one other management node (23) operating in the control plane of the wireless communication network for tracking of the unregistered wireless device (22) in at least one cell.

20. The method of any one of Claims 11-19, further comprising training a state machine using the collected data, the determination of the virtual identifier for the unregistered wireless device (22) being based on the trained state machine.

21. A computer storage device storing a computer program that, when executed by at least one processor (66) of a management node (23), causes the management node (23) to perform the method of any one of Claims 11-20.